Bottom-Up Tree Evaluation in Tree-Based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  title =        "Bottom-Up Tree Evaluation in Tree-Based Genetic
  author =       "Geng Li and Xiao-Jun Zeng",
  booktitle =    "Advances in Swarm Intelligence, First International
                 Conference, {ICSI} 2010, Beijing, China, June 12-15,
                 2010, Proceedings, Part {I}",
  publisher =    "Springer",
  year =         "2010",
  volume =       "6145",
  editor =       "Ying Tan and Yuhui Shi and Kay Chen Tan",
  isbn13 =       "978-3-642-13494-4",
  pages =        "513--522",
  series =       "Lecture Notes in Computer Science",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  DOI =          "doi:10.1007/978-3-642-13495-1_63",
  abstract =     "In tree-based genetic programming (GP) performance
                 optimisation, the primary optimization target is the
                 process of fitness evaluation. This is because fitness
                 evaluation takes most of execution time in GP. Standard
                 fitness evaluation uses the top-down tree evaluation
                 algorithm. Top-down tree evaluation evaluates program
                 tree from the root to the leaf of the tree. The
                 algorithm reflects the nature of computer program
                 execution and hence it is the most widely used tree
                 evaluation algorithm. In this paper, we identify a
                 scenario in tree evaluation where top-down evaluation
                 is costly and less effective. We then propose a new
                 tree evaluation algorithm called bottom-up tree
                 evaluation explicitly addressing the problem
                 identified. Both theoretical analysis and practical
                 experiments are performed to compare the performance of
                 bottom-up tree evaluation and top-down tree evaluation.
                 It is found that bottom-up tree evaluation algorithm
                 outperforms standard top-down tree evaluation when the
                 program tree depth is small.",
  bibdate =      "2010-06-10",
  bibsource =    "DBLP,

Genetic Programming entries for Geng Li Xiao-Jun Zeng